Trends by population
- removed samples that did not match to a Lab ID from the “FLOW ONLY” tab of “HRS sample list.xlsx”
- removed samples where date could not be parsed
- removed samples where EXPERIMENTER could not be parsed
## [1] "# Start of new population results"
## [1] "naive.Bcells.(CD27-.IgD+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "naive.Bcells.(CD27-.IgD+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for naive.Bcells.(CD27-.IgD+)"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.65306 -0.10234 0.03326 0.13416 0.35205
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.688e-01 2.883e-01 3.360 0.000783 ***
## DATE_MONTH -1.989e-05 1.675e-05 -1.188 0.235008
## MACHINELSR 2.284e-02 3.971e-03 5.750 9.19e-09 ***
## EXPERIMENTEREC -1.446e-02 8.078e-03 -1.790 0.073482 .
## EXPERIMENTERHB 3.869e-03 6.060e-03 0.638 0.523199
## EXPERIMENTERRR 6.276e-03 6.409e-03 0.979 0.327470
## EXPERIMENTERZF -5.257e-03 4.709e-03 -1.116 0.264295
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1743 on 9401 degrees of freedom
## Multiple R-squared: 0.005538, Adjusted R-squared: 0.004903
## F-statistic: 8.725 on 6 and 9401 DF, p-value: 1.688e-09
##
## [1] "Stepwise Linear Regression for naive.Bcells.(CD27-.IgD+)"
## Start: AIC=-32862.74
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE_MONTH 1 0.04286 285.69 -32863
## <none> 285.65 -32863
## - EXPERIMENTER 4 0.29832 285.95 -32861
## - MACHINE 1 1.00470 286.65 -32832
##
## Step: AIC=-32863.33
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 285.69 -32863
## + DATE_MONTH 1 0.04286 285.65 -32863
## - EXPERIMENTER 4 0.36225 286.05 -32859
## - MACHINE 1 1.20369 286.90 -32826
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 285.6491 -32862.74
## 2 - DATE_MONTH 1 0.04285724 9402 285.6920 -32863.33
## [1] "ANOVA of EXPERIMENTER for naive.Bcells.(CD27-.IgD+)"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.0224755594 -0.042094073 -0.002857046 0.0153168
## HB-DHS -0.0047638520 -0.020881866 0.011354162 0.9287569
## RR-DHS 0.0008956491 -0.015517111 0.017308409 0.9998898
## ZF-DHS -0.0053129934 -0.018043655 0.007417668 0.7859854
## HB-EC 0.0177117074 -0.003447220 0.038870635 0.1501405
## RR-EC 0.0233712085 0.001986903 0.044755514 0.0240070
## ZF-EC 0.0171625660 -0.001545175 0.035870307 0.0900059
## RR-HB 0.0056595011 -0.012566657 0.023885659 0.9157643
## ZF-HB -0.0005491414 -0.015545271 0.014446988 0.9999775
## ZF-RR -0.0062086426 -0.021521128 0.009103843 0.8033569
##
## [1] "ANOVA of MACHINE for naive.Bcells.(CD27-.IgD+)"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 1.19 1.1855 38.98 4.46e-10 ***
## Residuals 9406 286.05 0.0304
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Kruskal-Wallis test of MACHINE for naive.Bcells.(CD27-.IgD+)"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9388, df = 9390, p-value = 0.504
##
## [1] "# Start of new population results"
## [1] "cytotoxic.Tcells-CD8+"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "cytotoxic.Tcells-CD8+"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for cytotoxic.Tcells-CD8+"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24509 -0.08569 -0.02060 0.06459 0.66925
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.052e-01 1.960e-01 4.108 4.03e-05 ***
## DATE_MONTH -3.250e-05 1.139e-05 -2.855 0.00432 **
## MACHINELSR -2.696e-03 2.700e-03 -0.999 0.31805
## EXPERIMENTEREC 1.458e-03 5.492e-03 0.265 0.79066
## EXPERIMENTERHB 1.635e-03 4.120e-03 0.397 0.69150
## EXPERIMENTERRR 6.448e-03 4.357e-03 1.480 0.13889
## EXPERIMENTERZF 8.271e-03 3.201e-03 2.584 0.00979 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1185 on 9401 degrees of freedom
## Multiple R-squared: 0.001933, Adjusted R-squared: 0.001296
## F-statistic: 3.034 on 6 and 9401 DF, p-value: 0.00577
##
## [1] "Stepwise Linear Regression for cytotoxic.Tcells-CD8+"
## Start: AIC=-40124.73
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.01400 132.02 -40126
## <none> 132.01 -40125
## - EXPERIMENTER 4 0.11944 132.13 -40124
## - DATE_MONTH 1 0.11443 132.12 -40119
##
## Step: AIC=-40125.73
## TARGET_FREQ ~ DATE_MONTH + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.11180 132.13 -40126
## <none> 132.02 -40126
## + MACHINE 1 0.01400 132.01 -40125
## - DATE_MONTH 1 0.10129 132.12 -40121
##
## Step: AIC=-40125.77
## TARGET_FREQ ~ DATE_MONTH
##
## Df Sum of Sq RSS AIC
## <none> 132.13 -40126
## + EXPERIMENTER 4 0.111799 132.02 -40126
## + MACHINE 1 0.006361 132.13 -40124
## - DATE_MONTH 1 0.129847 132.26 -40119
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 132.0089 -40124.73
## 2 - MACHINE 1 0.01400045 9402 132.0229 -40125.73
## 3 - EXPERIMENTER 4 0.11179942 9406 132.1347 -40125.77
## [1] "ANOVA of EXPERIMENTER for cytotoxic.Tcells-CD8+"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.0055543657 -0.0188679565 0.007759225 0.7861987
## HB-DHS 0.0006185016 -0.0103195668 0.011556570 0.9998731
## RR-DHS 0.0022539959 -0.0088840943 0.013392086 0.9817063
## ZF-DHS 0.0069103911 -0.0017289392 0.015549721 0.1864234
## HB-EC 0.0061728673 -0.0081860853 0.020531820 0.7669435
## RR-EC 0.0078083616 -0.0067035381 0.022320261 0.5834058
## ZF-EC 0.0124647568 -0.0002307624 0.025160276 0.0572061
## RR-HB 0.0016354943 -0.0107332111 0.014004200 0.9963869
## ZF-HB 0.0062918895 -0.0038848412 0.016468620 0.4421505
## ZF-RR 0.0046563953 -0.0057350223 0.015047813 0.7382304
##
## [1] "ANOVA of MACHINE for cytotoxic.Tcells-CD8+"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.0 0.000528 0.038 0.846
## Residuals 9406 132.3 0.014062
## [1] "Kruskal-Wallis test of MACHINE for cytotoxic.Tcells-CD8+"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9407, df = 9407, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "Tcells.(CD3+.CD19-)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Tcells.(CD3+.CD19-)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for Tcells.(CD3+.CD19-)"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.69747 -0.07307 0.02298 0.09576 0.27474
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.005e-01 2.149e-01 4.190 2.82e-05 ***
## DATE_MONTH -1.236e-05 1.248e-05 -0.990 0.32201
## MACHINELSR 1.893e-02 2.960e-03 6.395 1.68e-10 ***
## EXPERIMENTEREC 3.198e-02 6.022e-03 5.311 1.12e-07 ***
## EXPERIMENTERHB 6.141e-03 4.517e-03 1.359 0.17404
## EXPERIMENTERRR -9.353e-03 4.777e-03 -1.958 0.05026 .
## EXPERIMENTERZF -9.493e-03 3.510e-03 -2.704 0.00686 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1299 on 9401 degrees of freedom
## Multiple R-squared: 0.0113, Adjusted R-squared: 0.01066
## F-statistic: 17.9 on 6 and 9401 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for Tcells.(CD3+.CD19-)"
## Start: AIC=-38390.87
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE_MONTH 1 0.01656 158.74 -38392
## <none> 158.72 -38391
## - MACHINE 1 0.69044 159.41 -38352
## - EXPERIMENTER 4 1.17917 159.90 -38329
##
## Step: AIC=-38391.89
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 158.74 -38392
## + DATE_MONTH 1 0.01656 158.72 -38391
## - MACHINE 1 0.80575 159.55 -38346
## - EXPERIMENTER 4 1.18241 159.92 -38330
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 158.7238 -38390.87
## 2 - DATE_MONTH 1 0.01656094 9402 158.7404 -38391.89
## [1] "ANOVA of EXPERIMENTER for Tcells.(CD3+.CD19-)"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.0262752806 0.011645183 0.0409053783 0.0000096
## HB-DHS -0.0007745432 -0.012794216 0.0112451298 0.9997866
## RR-DHS -0.0132419189 -0.025481393 -0.0010024452 0.0262907
## ZF-DHS -0.0093776414 -0.018871267 0.0001159841 0.0547535
## HB-EC -0.0270498238 -0.042828653 -0.0112709944 0.0000290
## RR-EC -0.0395171996 -0.055464100 -0.0235702990 0.0000000
## ZF-EC -0.0356529220 -0.049603830 -0.0217020137 0.0000000
## RR-HB -0.0124673758 -0.026059153 0.0011244019 0.0900855
## ZF-HB -0.0086030982 -0.019786149 0.0025799526 0.2205239
## ZF-RR 0.0038642776 -0.007554689 0.0152832445 0.8880081
##
## [1] "ANOVA of MACHINE for Tcells.(CD3+.CD19-)"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.61 0.6144 36.13 1.91e-09 ***
## Residuals 9406 159.92 0.0170
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Kruskal-Wallis test of MACHINE for Tcells.(CD3+.CD19-)"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9407, df = 9407, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "Live.cells.(PE-)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Live.cells.(PE-)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
## [1] "NA for Freq plot"
## [1] "# Start of new population results"
## [1] "IgD-.memory.Bcells.(CD27+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "IgD-.memory.Bcells.(CD27+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for IgD-.memory.Bcells.(CD27+)"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.13978 -0.06253 -0.02307 0.03374 0.66841
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.380e-01 1.541e-01 -3.492 0.000482 ***
## DATE_MONTH 3.939e-05 8.949e-06 4.401 1.09e-05 ***
## MACHINELSR -2.840e-02 2.122e-03 -13.383 < 2e-16 ***
## EXPERIMENTEREC 2.466e-03 4.316e-03 0.571 0.567861
## EXPERIMENTERHB -4.768e-03 3.238e-03 -1.472 0.140922
## EXPERIMENTERRR -1.055e-02 3.424e-03 -3.080 0.002075 **
## EXPERIMENTERZF -5.582e-03 2.516e-03 -2.218 0.026564 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.09314 on 9401 degrees of freedom
## Multiple R-squared: 0.02975, Adjusted R-squared: 0.02913
## F-statistic: 48.03 on 6 and 9401 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for IgD-.memory.Bcells.(CD27+)"
## Start: AIC=-44655.04
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 81.559 -44655
## - EXPERIMENTER 4 0.13626 81.696 -44647
## - DATE_MONTH 1 0.16802 81.727 -44638
## - MACHINE 1 1.55383 83.113 -44479
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 81.55938 -44655.04
## [1] "ANOVA of EXPERIMENTER for IgD-.memory.Bcells.(CD27+)"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.015779069 0.005182100 0.026376039 0.0004699
## HB-DHS 0.006823318 -0.001882852 0.015529487 0.2039392
## RR-DHS -0.001827190 -0.010692567 0.007038187 0.9804193
## ZF-DHS -0.004937097 -0.011813583 0.001939389 0.2864674
## HB-EC -0.008955752 -0.020384778 0.002473275 0.2040921
## RR-EC -0.017606260 -0.029157024 -0.006055495 0.0003119
## ZF-EC -0.020716166 -0.030821181 -0.010611152 0.0000002
## RR-HB -0.008650508 -0.018495394 0.001194379 0.1160545
## ZF-HB -0.011760415 -0.019860596 -0.003660233 0.0007165
## ZF-RR -0.003109907 -0.011380969 0.005161155 0.8435164
##
## [1] "ANOVA of MACHINE for IgD-.memory.Bcells.(CD27+)"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 2.16 2.1568 247.7 <2e-16 ***
## Residuals 9406 81.90 0.0087
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Kruskal-Wallis test of MACHINE for IgD-.memory.Bcells.(CD27+)"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9373.1, df = 9370, p-value = 0.4889
##
## [1] "# Start of new population results"
## [1] "IgD+.memory.Bcells.(CD27+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "IgD+.memory.Bcells.(CD27+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for IgD+.memory.Bcells.(CD27+)"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.14294 -0.07282 -0.02713 0.04301 0.58625
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.672e-01 1.672e-01 -1.000 0.3174
## DATE_MONTH 1.734e-05 9.713e-06 1.785 0.0742 .
## MACHINELSR -1.629e-03 2.303e-03 -0.707 0.4794
## EXPERIMENTEREC 1.045e-02 4.685e-03 2.231 0.0257 *
## EXPERIMENTERHB 6.534e-03 3.514e-03 1.859 0.0630 .
## EXPERIMENTERRR 3.294e-03 3.717e-03 0.886 0.3755
## EXPERIMENTERZF 4.531e-03 2.731e-03 1.659 0.0971 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1011 on 9401 degrees of freedom
## Multiple R-squared: 0.002011, Adjusted R-squared: 0.001374
## F-statistic: 3.157 on 6 and 9401 DF, p-value: 0.004289
##
## [1] "Stepwise Linear Regression for IgD+.memory.Bcells.(CD27+)"
## Start: AIC=-43114.57
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.005113 96.075 -43116
## - EXPERIMENTER 4 0.069841 96.139 -43116
## <none> 96.069 -43115
## - DATE_MONTH 1 0.032572 96.102 -43113
##
## Step: AIC=-43116.07
## TARGET_FREQ ~ DATE_MONTH + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.071569 96.146 -43117
## <none> 96.075 -43116
## + MACHINE 1 0.005113 96.069 -43115
## - DATE_MONTH 1 0.042851 96.117 -43114
##
## Step: AIC=-43117.07
## TARGET_FREQ ~ DATE_MONTH
##
## Df Sum of Sq RSS AIC
## <none> 96.146 -43117
## + EXPERIMENTER 4 0.071569 96.075 -43116
## + MACHINE 1 0.006841 96.139 -43116
## - DATE_MONTH 1 0.116888 96.263 -43108
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 96.06943 -43114.57
## 2 - MACHINE 1 0.005113369 9402 96.07454 -43116.07
## 3 - EXPERIMENTER 4 0.071569282 9406 96.14611 -43117.07
## [1] "ANOVA of EXPERIMENTER for IgD+.memory.Bcells.(CD27+)"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.0146592566 0.003303787 0.026014726 0.0039356
## HB-DHS 0.0080802037 -0.001249128 0.017409535 0.1256621
## RR-DHS 0.0058840609 -0.003615874 0.015383995 0.4402473
## ZF-DHS 0.0051597156 -0.002208969 0.012528400 0.3117104
## HB-EC -0.0065790529 -0.018826136 0.005668030 0.5849623
## RR-EC -0.0087751957 -0.021152730 0.003602339 0.2991283
## ZF-EC -0.0094995410 -0.020327843 0.001328761 0.1170896
## RR-HB -0.0021961428 -0.012745697 0.008353412 0.9796800
## ZF-HB -0.0029204881 -0.011600457 0.005759481 0.8900923
## ZF-RR -0.0007243453 -0.009587426 0.008138735 0.9994527
##
## [1] "ANOVA of MACHINE for IgD+.memory.Bcells.(CD27+)"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.03 0.03028 2.96 0.0854 .
## Residuals 9406 96.23 0.01023
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Kruskal-Wallis test of MACHINE for IgD+.memory.Bcells.(CD27+)"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9368.8, df = 9373, p-value = 0.5104
##
## [1] "# Start of new population results"
## [1] "Helper.Tcells-CD4+"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Helper.Tcells-CD4+"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for Helper.Tcells-CD4+"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.67557 -0.08388 0.02063 0.10137 0.29332
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.685e-01 2.316e-01 -0.728 0.46686
## DATE_MONTH 4.876e-05 1.345e-05 3.625 0.00029 ***
## MACHINELSR 7.053e-03 3.189e-03 2.212 0.02702 *
## EXPERIMENTEREC 4.046e-03 6.487e-03 0.624 0.53286
## EXPERIMENTERHB -3.551e-03 4.867e-03 -0.730 0.46566
## EXPERIMENTERRR -3.436e-03 5.146e-03 -0.668 0.50432
## EXPERIMENTERZF 2.507e-04 3.782e-03 0.066 0.94715
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.14 on 9401 degrees of freedom
## Multiple R-squared: 0.002447, Adjusted R-squared: 0.001811
## F-statistic: 3.844 on 6 and 9401 DF, p-value: 0.000783
##
## [1] "Stepwise Linear Regression for Helper.Tcells-CD4+"
## Start: AIC=-36989.55
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.042120 184.26 -36995
## <none> 184.22 -36990
## - MACHINE 1 0.095849 184.31 -36987
## - DATE_MONTH 1 0.257507 184.47 -36978
##
## Step: AIC=-36995.4
## TARGET_FREQ ~ DATE_MONTH + MACHINE
##
## Df Sum of Sq RSS AIC
## <none> 184.26 -36995
## - MACHINE 1 0.12489 184.38 -36991
## + EXPERIMENTER 4 0.04212 184.22 -36990
## - DATE_MONTH 1 0.37295 184.63 -36978
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 184.2172 -36989.55
## 2 - EXPERIMENTER 4 0.04212 9405 184.2593 -36995.40
## [1] "ANOVA of EXPERIMENTER for Helper.Tcells-CD4+"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.0141071880 -0.001625793 0.0298401689 0.1033109
## HB-DHS -0.0030106051 -0.015936376 0.0099151655 0.9693114
## RR-DHS 0.0025091170 -0.010653024 0.0156712580 0.9853673
## ZF-DHS 0.0023875634 -0.007821735 0.0125968615 0.9688558
## HB-EC -0.0171177931 -0.034086102 -0.0001494838 0.0467919
## RR-EC -0.0115980710 -0.028747121 0.0055509795 0.3475664
## ZF-EC -0.0117196246 -0.026722216 0.0032829667 0.2068172
## RR-HB 0.0055197221 -0.009096666 0.0201361097 0.8413970
## ZF-HB 0.0053981685 -0.006627912 0.0174242485 0.7369863
## ZF-RR -0.0001215536 -0.012401334 0.0121582270 0.9999999
##
## [1] "ANOVA of MACHINE for Helper.Tcells-CD4+"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.04 0.03688 1.879 0.17
## Residuals 9406 184.63 0.01963
## [1] "Kruskal-Wallis test of MACHINE for Helper.Tcells-CD4+"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9407, df = 9407, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "B.cells.(CD3-.CD19+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "B.cells.(CD3-.CD19+)"
## [1] "n=9408"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 731|
## |EC |FORTESSA | 372|
## |HB |FORTESSA | 907|
## |RR |FORTESSA | 574|
## |ZF |FORTESSA | 1019|
## |DHS |LSR | 1575|
## |EC |LSR | 421|
## |HB |LSR | 501|
## |RR |LSR | 755|
## |ZF |LSR | 2553|
## [1] "Linear Regression for B.cells.(CD3-.CD19+)"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.08873 -0.03174 -0.01229 0.01590 0.87427
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.174e-01 9.090e-02 -8.993 < 2e-16 ***
## DATE_MONTH 5.132e-05 5.280e-06 9.719 < 2e-16 ***
## MACHINELSR -6.682e-04 1.252e-03 -0.534 0.59350
## EXPERIMENTEREC -1.320e-02 2.547e-03 -5.184 2.22e-07 ***
## EXPERIMENTERHB 5.116e-03 1.910e-03 2.678 0.00742 **
## EXPERIMENTERRR 4.642e-03 2.020e-03 2.298 0.02159 *
## EXPERIMENTERZF 1.484e-02 1.484e-03 9.995 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05495 on 9401 degrees of freedom
## Multiple R-squared: 0.02805, Adjusted R-squared: 0.02742
## F-statistic: 45.21 on 6 and 9401 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for B.cells.(CD3-.CD19+)"
## Start: AIC=-54584.08
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.00086 28.388 -54586
## <none> 28.387 -54584
## - DATE_MONTH 1 0.28524 28.673 -54492
## - EXPERIMENTER 4 0.61645 29.004 -54390
##
## Step: AIC=-54585.8
## TARGET_FREQ ~ DATE_MONTH + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 28.388 -54586
## + MACHINE 1 0.00086 28.387 -54584
## - DATE_MONTH 1 0.31607 28.704 -54484
## - EXPERIMENTER 4 0.61559 29.004 -54392
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9401 28.38748 -54584.08
## 2 - MACHINE 1 0.0008603943 9402 28.38834 -54585.80
## [1] "ANOVA of EXPERIMENTER for B.cells.(CD3-.CD19+)"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.001381208 -0.0075867309 0.004824316 0.9739975
## HB-DHS 0.008331977 0.0032336957 0.013430259 0.0000816
## RR-DHS 0.011829698 0.0066381849 0.017021211 0.0000000
## ZF-DHS 0.016830034 0.0128032039 0.020856864 0.0000000
## HB-EC 0.009713185 0.0030204141 0.016405956 0.0007212
## RR-EC 0.013210905 0.0064468451 0.019974966 0.0000010
## ZF-EC 0.018211241 0.0122938041 0.024128679 0.0000000
## RR-HB 0.003497720 -0.0022673876 0.009262828 0.4619989
## ZF-HB 0.008498056 0.0037546374 0.013241475 0.0000103
## ZF-RR 0.005000336 0.0001568506 0.009843821 0.0390517
##
## [1] "ANOVA of MACHINE for B.cells.(CD3-.CD19+)"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.016 0.016049 5.171 0.023 *
## Residuals 9406 29.191 0.003103
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Kruskal-Wallis test of MACHINE for B.cells.(CD3-.CD19+)"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9407, df = 9407, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "Non.classical.monocytes"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Non.classical.monocytes"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for Non.classical.monocytes"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.05207 -0.02459 -0.01307 0.00487 0.81757
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.241e-01 9.249e-02 4.585 4.59e-06 ***
## DATE_MONTH -2.224e-05 5.372e-06 -4.141 3.49e-05 ***
## MACHINELSR 2.360e-03 1.282e-03 1.840 0.0658 .
## EXPERIMENTEREC -6.348e-03 2.589e-03 -2.452 0.0142 *
## EXPERIMENTERHB -3.260e-03 1.972e-03 -1.653 0.0983 .
## EXPERIMENTERRR 3.486e-03 2.045e-03 1.704 0.0883 .
## EXPERIMENTERZF 3.333e-03 1.513e-03 2.203 0.0276 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05582 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.008559, Adjusted R-squared: 0.007923
## F-statistic: 13.45 on 6 and 9346 DF, p-value: 3.014e-15
##
## [1] "Stepwise Linear Regression for Non.classical.monocytes"
## Start: AIC=-53970.82
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 29.123 -53971
## - MACHINE 1 0.010551 29.134 -53969
## - DATE_MONTH 1 0.053425 29.176 -53956
## - EXPERIMENTER 4 0.091775 29.215 -53949
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 29.12295 -53970.82
## [1] "ANOVA of EXPERIMENTER for Non.classical.monocytes"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.0117994049 -0.0180870968 -0.0055117130 0.0000031
## HB-DHS -0.0054177086 -0.0106602930 -0.0001751241 0.0387430
## RR-DHS 0.0001263972 -0.0051064852 0.0053592796 0.9999957
## ZF-DHS 0.0025797715 -0.0015111673 0.0066707103 0.4212702
## HB-EC 0.0063816963 -0.0004395685 0.0132029611 0.0795161
## RR-EC 0.0119258021 0.0051119912 0.0187396131 0.0000180
## ZF-EC 0.0143791764 0.0083974758 0.0203608770 0.0000000
## RR-HB 0.0055441058 -0.0003191393 0.0114073509 0.0741692
## ZF-HB 0.0079974801 0.0031260979 0.0128688623 0.0000743
## ZF-RR 0.0024533743 -0.0024075650 0.0073143136 0.6424964
##
## [1] "ANOVA of MACHINE for Non.classical.monocytes"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.06 0.05977 19.07 1.28e-05 ***
## Residuals 9351 29.32 0.00313
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for Non.classical.monocytes"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9295, df = 9289, p-value = 0.4805
##
## [1] "# Start of new population results"
## [1] "Myeloid.DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Myeloid.DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for Myeloid.DC"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.66823 -0.05705 0.03455 0.09659 0.25940
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.084e+00 2.328e-01 8.950 < 2e-16 ***
## DATE_MONTH -7.919e-05 1.352e-05 -5.857 4.87e-09 ***
## MACHINELSR -3.362e-02 3.227e-03 -10.418 < 2e-16 ***
## EXPERIMENTEREC -2.402e-02 6.517e-03 -3.685 0.000230 ***
## EXPERIMENTERHB -1.928e-02 4.963e-03 -3.884 0.000103 ***
## EXPERIMENTERRR -2.276e-02 5.148e-03 -4.421 9.92e-06 ***
## EXPERIMENTERZF -1.961e-02 3.808e-03 -5.148 2.68e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1405 on 9345 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.01955, Adjusted R-squared: 0.01892
## F-statistic: 31.06 on 6 and 9345 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for Myeloid.DC"
## Start: AIC=-36704
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 184.40 -36704
## - EXPERIMENTER 4 0.66628 185.07 -36678
## - DATE_MONTH 1 0.67691 185.08 -36672
## - MACHINE 1 2.14156 186.54 -36598
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9345 184.4036 -36704
## [1] "ANOVA of EXPERIMENTER for Myeloid.DC"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.036712811 -0.052613690 -0.0208119312 0.0000000
## HB-DHS -0.013630496 -0.026888746 -0.0003722454 0.0403783
## RR-DHS -0.029759591 -0.042993309 -0.0165258728 0.0000000
## ZF-DHS -0.023715012 -0.034061349 -0.0133686736 0.0000000
## HB-EC 0.023082315 0.005833073 0.0403315570 0.0024387
## RR-EC 0.006953220 -0.010277173 0.0241836128 0.8061021
## ZF-EC 0.012997799 -0.002128398 0.0281239968 0.1311184
## RR-HB -0.016129095 -0.030955749 -0.0013024415 0.0250359
## ZF-HB -0.010084516 -0.022403001 0.0022339692 0.1674095
## ZF-RR 0.006044579 -0.006247498 0.0183366571 0.6650842
##
## [1] "ANOVA of MACHINE for Myeloid.DC"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 1.48 1.477 74.03 <2e-16 ***
## Residuals 9350 186.60 0.020
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for Myeloid.DC"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9312.8, df = 9306, p-value = 0.4781
##
## [1] "# Start of new population results"
## [1] "DC.NK"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "DC.NK"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for DC.NK"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.51338 -0.11598 0.00488 0.12237 0.46382
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.088e+00 2.714e-01 7.695 1.56e-14 ***
## DATE_MONTH -8.931e-05 1.576e-05 -5.667 1.50e-08 ***
## MACHINELSR -3.182e-02 3.762e-03 -8.456 < 2e-16 ***
## EXPERIMENTEREC 8.485e-02 7.597e-03 11.168 < 2e-16 ***
## EXPERIMENTERHB 3.637e-02 5.786e-03 6.286 3.41e-10 ***
## EXPERIMENTERRR 4.280e-02 6.002e-03 7.132 1.06e-12 ***
## EXPERIMENTERZF 8.581e-03 4.440e-03 1.933 0.0533 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1638 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.02654, Adjusted R-squared: 0.02592
## F-statistic: 42.47 on 6 and 9346 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for DC.NK"
## Start: AIC=-33835.24
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 250.73 -33835
## - DATE_MONTH 1 0.8614 251.59 -33805
## - MACHINE 1 1.9184 252.65 -33766
## - EXPERIMENTER 4 4.3577 255.09 -33682
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 250.7295 -33835.24
## [1] "ANOVA of EXPERIMENTER for DC.NK"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.069567513 0.051062276 0.088072750 0.0000000
## HB-DHS 0.040813932 0.025384539 0.056243324 0.0000000
## RR-DHS 0.034203386 0.018802547 0.049604224 0.0000000
## ZF-DHS 0.004165315 -0.007874682 0.016205312 0.8797150
## HB-EC -0.028753581 -0.048829171 -0.008677992 0.0008914
## RR-EC -0.035364127 -0.055417779 -0.015310475 0.0000150
## ZF-EC -0.065402198 -0.083006875 -0.047797521 0.0000000
## RR-HB -0.006610546 -0.023866598 0.010645506 0.8342594
## ZF-HB -0.036648617 -0.050985528 -0.022311705 0.0000000
## ZF-RR -0.030038071 -0.044344247 -0.015731894 0.0000001
##
## [1] "ANOVA of MACHINE for DC.NK"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 2.48 2.4775 90.82 <2e-16 ***
## Residuals 9351 255.09 0.0273
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for DC.NK"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9352, df = 9351, p-value = 0.4951
##
## [1] "# Start of new population results"
## [1] "MONOCYTES"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "MONOCYTES"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for MONOCYTES"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.31431 -0.10437 -0.01319 0.08793 0.69473
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.908e-01 2.309e-01 2.559 0.01051 *
## DATE_MONTH -1.643e-05 1.341e-05 -1.225 0.22051
## MACHINELSR 7.122e-03 3.201e-03 2.225 0.02610 *
## EXPERIMENTEREC -6.815e-02 6.463e-03 -10.545 < 2e-16 ***
## EXPERIMENTERHB -4.984e-02 4.922e-03 -10.126 < 2e-16 ***
## EXPERIMENTERRR -4.568e-02 5.105e-03 -8.948 < 2e-16 ***
## EXPERIMENTERZF -1.415e-02 3.777e-03 -3.747 0.00018 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1393 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.03008, Adjusted R-squared: 0.02945
## F-statistic: 48.3 on 6 and 9346 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for MONOCYTES"
## Start: AIC=-36860.89
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE_MONTH 1 0.0291 181.46 -36861
## <none> 181.43 -36861
## - MACHINE 1 0.0961 181.53 -36858
## - EXPERIMENTER 4 3.7338 185.16 -36678
##
## Step: AIC=-36861.39
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 181.46 -36861
## + DATE_MONTH 1 0.0291 181.43 -36861
## - MACHINE 1 0.1373 181.60 -36856
## - EXPERIMENTER 4 4.8979 186.36 -36620
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 181.4316 -36860.89
## 2 - DATE_MONTH 1 0.02914391 9347 181.4607 -36861.39
## [1] "ANOVA of EXPERIMENTER for MONOCYTES"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.07303406 -0.088712778 -0.057355336 0.0000000
## HB-DHS -0.05314144 -0.066214122 -0.040068750 0.0000000
## RR-DHS -0.04880055 -0.061849040 -0.035752053 0.0000000
## ZF-DHS -0.01452548 -0.024726467 -0.004324485 0.0009773
## HB-EC 0.01989262 0.002883405 0.036901837 0.0123982
## RR-EC 0.02423351 0.007242881 0.041224140 0.0009523
## ZF-EC 0.05850858 0.043592866 0.073424296 0.0000000
## RR-HB 0.00434089 -0.010279449 0.018961229 0.9276403
## ZF-HB 0.03861596 0.026468888 0.050763032 0.0000000
## ZF-RR 0.03427507 0.022154038 0.046396102 0.0000000
##
## [1] "ANOVA of MACHINE for MONOCYTES"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.7 0.6990 35.07 3.29e-09 ***
## Residuals 9351 186.4 0.0199
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for MONOCYTES"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9352, df = 9352, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "NK"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "NK"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for NK"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.60541 -0.09680 0.02125 0.11848 0.40552
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.484e+00 2.666e-01 9.317 < 2e-16 ***
## DATE_MONTH -1.093e-04 1.548e-05 -7.061 1.77e-12 ***
## MACHINELSR -1.126e-02 3.696e-03 -3.045 0.00233 **
## EXPERIMENTEREC 4.794e-02 7.463e-03 6.423 1.40e-10 ***
## EXPERIMENTERHB 1.019e-02 5.684e-03 1.794 0.07292 .
## EXPERIMENTERRR -1.622e-03 5.896e-03 -0.275 0.78328
## EXPERIMENTERZF 8.076e-03 4.361e-03 1.852 0.06408 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1609 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.009012, Adjusted R-squared: 0.008376
## F-statistic: 14.17 on 6 and 9346 DF, p-value: 3.939e-16
##
## [1] "Stepwise Linear Regression for NK"
## Start: AIC=-34168.73
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 241.95 -34169
## - MACHINE 1 0.24008 242.19 -34161
## - EXPERIMENTER 4 1.35656 243.30 -34124
## - DATE_MONTH 1 1.29071 243.24 -34121
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 241.9469 -34168.73
## [1] "ANOVA of EXPERIMENTER for NK"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.024798879 0.006651999 0.0429457595 0.0018132
## HB-DHS 0.006843907 -0.008286693 0.0219745069 0.7313985
## RR-DHS -0.015429191 -0.030531790 -0.0003265921 0.0424370
## ZF-DHS 0.003603776 -0.008203065 0.0154106161 0.9205084
## HB-EC -0.017954973 -0.037641795 0.0017318498 0.0933148
## RR-EC -0.040228071 -0.059893381 -0.0205627606 0.0000002
## ZF-EC -0.021195104 -0.038458864 -0.0039313441 0.0072617
## RR-HB -0.022273098 -0.039194984 -0.0053512119 0.0030526
## ZF-HB -0.003240131 -0.017299406 0.0108191438 0.9704707
## ZF-RR 0.019032967 0.005003831 0.0330621024 0.0020118
##
## [1] "ANOVA of MACHINE for NK"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.05 0.04879 1.869 0.172
## Residuals 9351 244.10 0.02610
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for NK"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9348.8, df = 9348, p-value = 0.4957
##
## [1] "# Start of new population results"
## [1] "DC.NK.MONOCYTES"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "DC.NK.MONOCYTES"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for DC.NK.MONOCYTES"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.28408 -0.09352 -0.02409 0.07163 0.67796
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.700e-01 2.116e-01 -1.748 0.08047 .
## DATE_MONTH 3.797e-05 1.229e-05 3.089 0.00201 **
## MACHINELSR 9.042e-03 2.934e-03 3.082 0.00206 **
## EXPERIMENTEREC -5.512e-02 5.924e-03 -9.304 < 2e-16 ***
## EXPERIMENTERHB -2.638e-02 4.511e-03 -5.847 5.17e-09 ***
## EXPERIMENTERRR -2.441e-02 4.680e-03 -5.215 1.87e-07 ***
## EXPERIMENTERZF -9.735e-03 3.462e-03 -2.812 0.00493 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1277 on 9347 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.01298, Adjusted R-squared: 0.01235
## F-statistic: 20.49 on 6 and 9347 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for DC.NK.MONOCYTES"
## Start: AIC=-38491.75
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 152.48 -38492
## - MACHINE 1 0.15497 152.64 -38484
## - DATE_MONTH 1 0.15568 152.64 -38484
## - EXPERIMENTER 4 1.67704 154.16 -38397
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9347 152.4837 -38491.75
## [1] "ANOVA of EXPERIMENTER for DC.NK.MONOCYTES"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.047902860 -0.062279794 -0.033525925 0.0000000
## HB-DHS -0.026843467 -0.038830443 -0.014856492 0.0000000
## RR-DHS -0.020218058 -0.032182846 -0.008253270 0.0000401
## ZF-DHS -0.008006740 -0.017360027 0.001346547 0.1337869
## HB-EC 0.021059392 0.005461543 0.036657242 0.0021537
## RR-EC 0.027684802 0.012103997 0.043265607 0.0000125
## ZF-EC 0.039896120 0.026218060 0.053574179 0.0000000
## RR-HB 0.006625409 -0.006781784 0.020032603 0.6608873
## ZF-HB 0.018836727 0.007697578 0.029975877 0.0000394
## ZF-RR 0.012211318 0.001096048 0.023326588 0.0228958
##
## [1] "ANOVA of MACHINE for DC.NK.MONOCYTES"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.29 0.28599 17.34 3.15e-05 ***
## Residuals 9352 154.20 0.01649
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 2 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for DC.NK.MONOCYTES"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9353, df = 9353, p-value = 0.4981
##
## [1] "# Start of new population results"
## [1] "NK.CD56HI"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "NK.CD56HI"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for NK.CD56HI"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.00980 -0.00631 -0.00367 0.00087 0.35773
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.846e-02 2.657e-02 1.824 0.0682 .
## DATE_MONTH -2.269e-06 1.543e-06 -1.470 0.1416
## MACHINELSR -2.635e-04 3.683e-04 -0.715 0.4744
## EXPERIMENTEREC -9.534e-04 7.439e-04 -1.282 0.2000
## EXPERIMENTERHB -1.116e-03 5.665e-04 -1.970 0.0488 *
## EXPERIMENTERRR -2.059e-04 5.878e-04 -0.350 0.7262
## EXPERIMENTERZF -1.101e-03 4.347e-04 -2.533 0.0113 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01603 on 9342 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.001343, Adjusted R-squared: 0.0007011
## F-statistic: 2.093 on 6 and 9342 DF, p-value: 0.05071
##
## [1] "Stepwise Linear Regression for NK.CD56HI"
## Start: AIC=-77277.82
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.00013148 2.4005 -77279
## <none> 2.4004 -77278
## - DATE_MONTH 1 0.00055527 2.4009 -77278
## - EXPERIMENTER 4 0.00228841 2.4027 -77277
##
## Step: AIC=-77279.31
## TARGET_FREQ ~ DATE_MONTH + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE_MONTH 1 0.00045140 2.4010 -77280
## <none> 2.4005 -77279
## - EXPERIMENTER 4 0.00227715 2.4028 -77278
## + MACHINE 1 0.00013148 2.4004 -77278
##
## Step: AIC=-77279.55
## TARGET_FREQ ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 2.4010 -77280
## + DATE_MONTH 1 4.514e-04 2.4005 -77279
## + MACHINE 1 2.762e-05 2.4009 -77278
## - EXPERIMENTER 4 2.644e-03 2.4036 -77277
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9342 2.400400 -77277.82
## 2 - MACHINE 1 0.0001314842 9343 2.400531 -77279.31
## 3 - DATE_MONTH 1 0.0004514006 9344 2.400982 -77279.55
## [1] "ANOVA of EXPERIMENTER for NK.CD56HI"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.0014292355 -0.0032327391 3.742682e-04 0.1943166
## HB-DHS -0.0011766589 -0.0026805066 3.271888e-04 0.2053982
## RR-DHS -0.0004894642 -0.0019908764 1.011948e-03 0.9009177
## ZF-DHS -0.0011955100 -0.0023691912 -2.182881e-05 0.0434331
## HB-EC 0.0002525765 -0.0017036369 2.208790e-03 0.9967061
## RR-EC 0.0009397713 -0.0010145705 2.894113e-03 0.6837886
## ZF-EC 0.0002337255 -0.0014817164 1.949167e-03 0.9959421
## RR-HB 0.0006871947 -0.0009945853 2.368975e-03 0.7988129
## ZF-HB -0.0000188511 -0.0014158740 1.378172e-03 0.9999996
## ZF-RR -0.0007060458 -0.0021004467 6.883550e-04 0.6396343
##
## [1] "ANOVA of MACHINE for NK.CD56HI"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.000 5.040e-06 0.02 0.889
## Residuals 9347 2.404 2.571e-04
## 7 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for NK.CD56HI"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9162.1, df = 9163, p-value = 0.5007
##
## [1] "# Start of new population results"
## [1] "NK.CD56LO"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "NK.CD56LO"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for NK.CD56LO"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.94093 -0.01152 0.02128 0.03991 0.07556
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.224e+00 1.268e-01 9.652 < 2e-16 ***
## DATE_MONTH -1.749e-05 7.366e-06 -2.375 0.01757 *
## MACHINELSR 6.947e-03 1.758e-03 3.952 7.81e-05 ***
## EXPERIMENTEREC 1.932e-02 3.550e-03 5.442 5.40e-08 ***
## EXPERIMENTERHB 4.689e-03 2.704e-03 1.734 0.08291 .
## EXPERIMENTERRR 3.782e-03 2.805e-03 1.348 0.17767
## EXPERIMENTERZF 5.759e-03 2.075e-03 2.775 0.00552 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07651 on 9342 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.005738, Adjusted R-squared: 0.005099
## F-statistic: 8.986 on 6 and 9342 DF, p-value: 8.207e-10
##
## [1] "Stepwise Linear Regression for NK.CD56LO"
## Start: AIC=-48053.94
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 54.681 -48054
## - DATE_MONTH 1 0.033015 54.714 -48050
## - MACHINE 1 0.091413 54.773 -48040
## - EXPERIMENTER 4 0.186301 54.867 -48030
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9342 54.68111 -48053.94
## [1] "ANOVA of EXPERIMENTER for NK.CD56LO"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.0142105287 0.0055906336 0.0228304237 0.0000681
## HB-DHS 0.0013678142 -0.0058198669 0.0085554954 0.9854625
## RR-DHS 0.0005311845 -0.0066448562 0.0077072251 0.9996301
## ZF-DHS 0.0053294921 -0.0002801492 0.0109391335 0.0718680
## HB-EC -0.0128427144 -0.0221924900 -0.0034929389 0.0016834
## RR-EC -0.0136793442 -0.0230201740 -0.0043385144 0.0006218
## ZF-EC -0.0088810366 -0.0170800376 -0.0006820355 0.0260154
## RR-HB -0.0008366298 -0.0088747434 0.0072014838 0.9985807
## ZF-HB 0.0039616779 -0.0027154314 0.0106387871 0.4852875
## ZF-RR 0.0047983077 -0.0018662693 0.0114628847 0.2836929
##
## [1] "ANOVA of MACHINE for NK.CD56LO"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.13 0.12891 21.96 2.82e-06 ***
## Residuals 9347 54.87 0.00587
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for NK.CD56LO"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9325.3, df = 9328, p-value = 0.5058
##
## [1] "# Start of new population results"
## [1] "Plasmacytoid.DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Plasmacytoid.DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for Plasmacytoid.DC"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.18066 -0.08346 -0.03152 0.04447 0.79902
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.748e-02 2.022e-01 -0.136 0.891893
## DATE_MONTH 1.125e-05 1.174e-05 0.958 0.338144
## MACHINELSR 1.337e-02 2.803e-03 4.770 1.87e-06 ***
## EXPERIMENTEREC 2.347e-02 5.660e-03 4.147 3.40e-05 ***
## EXPERIMENTERHB 1.388e-02 4.310e-03 3.221 0.001281 **
## EXPERIMENTERRR 1.481e-02 4.472e-03 3.311 0.000932 ***
## EXPERIMENTERZF 1.203e-02 3.308e-03 3.638 0.000276 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.122 on 9345 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.005568, Adjusted R-squared: 0.004929
## F-statistic: 8.72 on 6 and 9345 DF, p-value: 1.71e-09
##
## [1] "Stepwise Linear Regression for Plasmacytoid.DC"
## Start: AIC=-39340.16
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE_MONTH 1 0.01366 139.12 -39341
## <none> 139.11 -39340
## - EXPERIMENTER 4 0.35403 139.46 -39324
## - MACHINE 1 0.33864 139.45 -39319
##
## Step: AIC=-39341.25
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 139.12 -39341
## + DATE_MONTH 1 0.01366 139.11 -39340
## - MACHINE 1 0.32685 139.45 -39321
## - EXPERIMENTER 4 0.50423 139.62 -39315
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9345 139.1071 -39340.16
## 2 - DATE_MONTH 1 0.01365841 9346 139.1208 -39341.25
## [1] "ANOVA of EXPERIMENTER for Plasmacytoid.DC"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.023900493 0.010159798 0.037641187 0.0000208
## HB-DHS 0.010355743 -0.001101332 0.021812818 0.0985207
## RR-DHS 0.014783890 0.003348014 0.026219765 0.0038649
## ZF-DHS 0.012908715 0.003967960 0.021849470 0.0007842
## HB-EC -0.013544749 -0.028450627 0.001361129 0.0954225
## RR-EC -0.009116603 -0.024006193 0.005772987 0.4523895
## ZF-EC -0.010991777 -0.024063033 0.002079478 0.1467200
## RR-HB 0.004428146 -0.008384260 0.017240553 0.8800985
## ZF-HB 0.002552972 -0.008092008 0.013197952 0.9658797
## ZF-RR -0.001875175 -0.012497335 0.008746986 0.9890470
##
## [1] "ANOVA of MACHINE for Plasmacytoid.DC"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.26 0.26096 17.48 2.94e-05 ***
## Residuals 9350 139.62 0.01493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for Plasmacytoid.DC"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9279.8, df = 9285, p-value = 0.5133
##
## [1] "# Start of new population results"
## [1] "Classical.monocytes"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Classical.monocytes"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for Classical.monocytes"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81731 -0.00458 0.01349 0.02498 0.05157
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.752e-01 9.417e-02 6.108 1.05e-09 ***
## DATE_MONTH 2.223e-05 5.469e-06 4.064 4.86e-05 ***
## MACHINELSR -1.964e-03 1.306e-03 -1.504 0.1326
## EXPERIMENTEREC 6.390e-03 2.636e-03 2.424 0.0154 *
## EXPERIMENTERHB 2.100e-03 2.008e-03 1.046 0.2955
## EXPERIMENTERRR -4.115e-03 2.083e-03 -1.976 0.0482 *
## EXPERIMENTERZF -3.317e-03 1.541e-03 -2.153 0.0313 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05683 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.007629, Adjusted R-squared: 0.006992
## F-statistic: 11.97 on 6 and 9346 DF, p-value: 1.933e-13
##
## [1] "Stepwise Linear Regression for Classical.monocytes"
## Start: AIC=-53634.41
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 30.189 -53634
## - MACHINE 1 0.007306 30.197 -53634
## - DATE_MONTH 1 0.053352 30.243 -53620
## - EXPERIMENTER 4 0.086884 30.276 -53616
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 30.18952 -53634.41
## [1] "ANOVA of EXPERIMENTER for Classical.monocytes"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS 0.0117745141 0.005373670 0.0181753585 0.0000053
## HB-DHS 0.0041312273 -0.001205702 0.0094681567 0.2149294
## RR-DHS -0.0008045795 -0.006131632 0.0045224732 0.9939610
## ZF-DHS -0.0025511539 -0.006715713 0.0016134049 0.4518631
## HB-EC -0.0076432868 -0.014587306 -0.0006992674 0.0224987
## RR-EC -0.0125790936 -0.019515525 -0.0056426622 0.0000076
## ZF-EC -0.0143256680 -0.020415014 -0.0082363215 0.0000000
## RR-HB -0.0049358068 -0.010904566 0.0010329525 0.1594713
## ZF-HB -0.0066823812 -0.011641428 -0.0017233342 0.0022136
## ZF-RR -0.0017465744 -0.006694991 0.0032018417 0.8717320
##
## [1] "ANOVA of MACHINE for Classical.monocytes"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.047 0.04681 14.41 0.000148 ***
## Residuals 9351 30.375 0.00325
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for Classical.monocytes"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9314.2, df = 9320, p-value = 0.5149
##
## [1] "# Start of new population results"
## [1] "Live.immune.cells"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Live.immune.cells"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
## [1] "NA for Freq plot"
## [1] "# Start of new population results"
## [1] "Live.Single.PBMCs"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "Live.Single.PBMCs"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
## [1] "NA for Freq plot"
## [1] "# Start of new population results"
## [1] "DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time COUNT"
## [1] "DC"
## [1] "n=9356"
## [1] "PLOT TYPE = Machine Time FREQ"
##
##
## |Var1 |Var2 | Freq|
## |:----|:--------|----:|
## |DHS |FORTESSA | 705|
## |EC |FORTESSA | 373|
## |HB |FORTESSA | 846|
## |RR |FORTESSA | 581|
## |ZF |FORTESSA | 989|
## |DHS |LSR | 1567|
## |EC |LSR | 421|
## |HB |LSR | 503|
## |RR |LSR | 777|
## |ZF |LSR | 2594|
## [1] "Linear Regression for DC"
##
## Call:
## lm(formula = formula, data = subF)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.18140 -0.06750 -0.02255 0.04244 0.84416
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.663e-01 1.670e-01 -1.594 0.11088
## DATE_MONTH 2.620e-05 9.699e-06 2.701 0.00693 **
## MACHINELSR -7.619e-03 2.315e-03 -3.290 0.00100 **
## EXPERIMENTEREC -5.808e-02 4.675e-03 -12.423 < 2e-16 ***
## EXPERIMENTERHB -2.094e-02 3.561e-03 -5.881 4.21e-09 ***
## EXPERIMENTERRR -3.423e-02 3.693e-03 -9.269 < 2e-16 ***
## EXPERIMENTERZF -2.851e-02 2.732e-03 -10.436 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1008 on 9346 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.02313, Adjusted R-squared: 0.0225
## F-statistic: 36.88 on 6 and 9346 DF, p-value: < 2.2e-16
##
## [1] "Stepwise Linear Regression for DC"
## Start: AIC=-42917.53
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 94.947 -42918
## - DATE_MONTH 1 0.07412 95.021 -42912
## - MACHINE 1 0.11000 95.057 -42909
## - EXPERIMENTER 4 1.98191 96.929 -42732
## Stepwise Model Path
## Analysis of Deviance Table
##
## Initial Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
## Final Model:
## TARGET_FREQ ~ DATE_MONTH + MACHINE + EXPERIMENTER
##
##
## Step Df Deviance Resid. Df Resid. Dev AIC
## 1 9346 94.94687 -42917.53
## [1] "ANOVA of EXPERIMENTER for DC"
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = formula, data = subF)
##
## $EXPERIMENTER
## diff lwr upr p adj
## EC-DHS -0.050881216 -0.062233177 -0.039529255 0.0000000
## HB-DHS -0.016863607 -0.026328704 -0.007398510 0.0000117
## RR-DHS -0.029702199 -0.039149779 -0.020254618 0.0000000
## ZF-DHS -0.027787911 -0.035173797 -0.020402025 0.0000000
## HB-EC 0.034017609 0.021702322 0.046332896 0.0000000
## RR-EC 0.021179017 0.008877187 0.033480847 0.0000264
## ZF-EC 0.023093305 0.012293788 0.033892821 0.0000001
## RR-HB -0.012838592 -0.023424246 -0.002252938 0.0083492
## ZF-HB -0.010924304 -0.019719223 -0.002129385 0.0063346
## ZF-RR 0.001914288 -0.006861777 0.010690353 0.9758562
##
## [1] "ANOVA of MACHINE for DC"
## Df Sum Sq Mean Sq F value Pr(>F)
## MACHINE 1 0.13 0.13039 12.56 0.000396 ***
## Residuals 9351 97.06 0.01038
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "Kruskal-Wallis test of MACHINE for DC"
##
## Kruskal-Wallis rank sum test
##
## data: MACHINE by TARGET_FREQ
## Kruskal-Wallis chi-squared = 9345.6, df = 9346, p-value = 0.4993